Arturo provides on-demand physical property characteristics and predictions for residential and commercial properties. This talk will discuss how Arturo leverages the scaleability of Cloud Optimized GeoTiffs (COG) and the interoperability of STAC to build an event-driven data pipeline which feeds the most current satellite, aerial, and ground-level imagery into our deep learning models. We will also demo an asynchronous COG tiler (TMS/WMTS/WMS) which will be open sourced prior to the conference and serves map tiles and static images from COGs indexed in a STAC catalog.
I'm a spatial data engineer at Arturo.ai with a background in geospatial intelligence. I started working with open source geospatial software as a means to learn how to code and have since become passionate about contributing to and building integrations between different open source communities (like STAC and COG).